As @itamarst points out, Dask runs on top of NumPy, which is why I didn’t include it in the ecosystem comparison. I did include libraries that use multithreading and achieve comparable performance.

The main bottleneck of this algo is memory access. Since the single-threaded batched implementation can already generate substantial memory-level parallelism, adding threads may not improve throughput much on the same machine. It’s worth benchmarking, though!

Using multiple machines would be a different story.

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Exactly! There is also the tension between a simpler title and a super exact one. We could have a title that is “Making np.searchsorted (up to) 25x faster (when querying multiple keys)”.

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Thanks for sharing! Author here if you have questions :)

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